天山北坡不同环境条件下雪岭云杉(Picea schrenkiana)林限土壤属性

为了研究干旱区天山北坡中山带长达1000余公里的单建群种山地针叶林的空间分布原因,选择精河、玛纳斯、阜康和巴里坤中山带作为四种不同的环境条件,通过对不同环境条件雪岭云杉(Picea schrenkiana)上、下限土壤的采样与分析,探讨土壤因素对天山北坡中山带雪岭云杉分布的控制作用.雪岭云杉在天山北坡的连续分布主要是水热组合条件和土壤因素相互作用的结果,上、下限土壤属性变化与环境条件变化间存在着紧密的联系,表现为降雨量丰富的玛纳斯林区土壤肥力较高,但CaCO3含量较低,而降雨量较小的巴里坤和精河林区土壤肥力较差,但CaCO3含量较高.虽然长达1000余公里的雪岭云杉中山带环境条件差异较大,但其土壤属性变化均在雪岭云杉发育所需土壤条件的允许范围之内,这主要是受土壤成土母质、不同海拔高度的降雨量、地形、局地环流等因素的共同影响.     

固沙树种梭梭在不同水分梯度下的光合生理特征

对不同水分梯度下梭梭光合作用的研究发现,地下水位、土壤含水量、灌水量对梭梭的光合具有明显的影响。在1．4m、2．4m、3．4m地下水位下,梭梭的光合速率、呼吸作用、量子效率随水位的降低而降低,光补偿点随水位的降低而增大;在滴灌供水时,梭梭的光合速率较对照明显提高,且灌水量越大,梭梭的光合速率越高;半流动沙丘、丘间低地、粘土沙障固定沙丘退化梭梭的光合作用的强弱同其林地土壤水分的高低基本一致。7月,不同水分梯度下的梭梭光合作用均表现出午休现象,9月只有立地条件较差的梭梭发生光合午休,而且9月光合作用要强于7月,说明9月环境条件更有利于梭梭生长。     

Will a 385 million year‐struggle for light become a struggle for water and for carbon? – How trees may cope with more frequent climate change‐type drought events

Trees are exceptional organisms that have evolved over some 385 million years and have overtaken other plants in order to harvest light first. However, this advantage comes with a cost: trees must transport water all the way up to their crowns and inherent physical limitations make them vulnerable to water deficits. Because climate change scenarios predict more frequent extreme drought events, trees will increasingly need to cope with water stress. Recent occurrences of climate change‐type droughts have had severe impacts on several forest ecosystems. Initial experimental studies have been undertaken and show that stomatal control of water loss hinders carbon assimilation and could lead to starvation during droughts. Other mechanisms of drought‐induced mortality are catastrophic xylem dysfunction, impeded long‐distance transport of carbohydrates (translocation) and also symplastic failure (cellular breakdown). However, direct empirical support is absent for either hypothesis. More experimental studies are necessary to increase our understanding of these processes and to resolve the mystery of drought‐related tree mortality. Instead of testing the validity of particular hypothesis as mechanisms of drought‐induced tree mortality, future research should aim at revealing the temporal dynamics of these mechanisms in different species and over a gradient of environmental conditions. Only such studies will reveal whether the struggle for light will become a struggle for water and/or for carbon in drought‐affected areas.     

山桐子实生优树选择研究初报

以四川等8个省份的山桐子野生资源为研究对象,通过实地走访和调查,了解山桐子资源分布状况和生态环境,利用产量、含油率等经济性状对山桐子野生群体进行优株选择。结果表明:安徽、江苏、浙江、江西各地主要以山桐子分布,而湖北、湖南、陕西、四川等地主要以山桐子的变异类型——毛叶山桐子为主,其中四川省毛叶山桐子分布较为密集;通过对各地点气候条件和土壤条件分析得出,山桐子适应性强,对气候要求不严,适合在微酸性土壤生长,尤喜肥沃土壤;根据能源油料植物原则对山桐子提出选优标准,从234株山桐子实生树中初步选择43个单株;主成分分析和聚类分析结果将43个单株划分为最高产量、较高产量和中产量3大类,且所有单株的单株产量、单位面积产量和全果含油率3个主要经济指标均高出群体平均值20%以上。本研究为山桐子种质资源收集与评价、优良种质或品种的选育奠定了重要基础。     

柳州市行道树资源调查与结构特征分析

该研究通过对柳州市区主要道路园林绿化全面踏勘,在四城区中筛选出68条道路行道树进行现场调查和综合评价。结果表明:(1)柳州市行道树共有28种,隶属于17科21属,常绿树种与落叶树种比例及乡土树种与外来树种比例合理。(2)柳州市行道树中小叶榕和黄葛榕在各城区应用频度较高,树种组成结构相对单一。(3)季相树种在各城区应用频度不均衡,部分城区春季景观营造效果显著,而夏秋冬季相景观效果不显著。(4)绿化达标率和林荫路推广率离国家生态园林城市还有较大差距,物种丰富度和多样性指数有待提高。建议加大乡土树种的应用与推广,提高各城区物种丰富度及季相树种的应用,营造城市道路特色季相景观。该研究成果提出了发展乡土树种、丰富树种多样性及季相景观营造的技术建议,对柳州市行道树树种规划和建设提供了科学依据。     

B型烟粉虱在四种葫芦科寄主植物上的发育和繁殖

研究了B型烟粉虱在4种葫芦科寄主植物黄瓜、节瓜、苦瓜和丝瓜上的发育和繁殖特性.结果表明,B型烟粉虱在节瓜上的世代发育历期最短,为19.3 d,在苦瓜上的世代发育历期最长,为29.0 d;世代存活率在黄瓜上最高,为92.85％,在苦瓜上最低,为53.08％;平均单雌产卵量在黄瓜上最多,为187.4粒,苦瓜上最少,为30.0粒;雌成虫寿命以在黄瓜上最长,为25.2 d,在苦瓜上最短,为10.9 d.B型烟粉虱在黄瓜、节瓜、苦瓜和丝瓜上的内禀增长率（r_m）分别为0.1453、0.1429、0.0616和0.1055.综合比较4种葫芦科植物,黄瓜是B型烟粉虱的最适宜寄主.     

基于Web的中国昆虫科级鉴别分类系统InsectID的设计与开发

详细介绍了国内首个昆虫科级鉴别分类网络系统InsectID(见http://insectx.3322.org)的设计思路、各组成部分的结构与功能,讨论了开发过程中分类检索表的转化与再现、系统分类树与特征解释机制的实现等关键问题。该系统具有分类单元全面、信息可靠、鉴定简单、扩充性强、更新便捷等诸多优点,是昆虫分类研究与教学的有力工具,也适用于其他生物分类系统的构建。     

中国几种剧毒鹅膏菌的ITS序列分析

测定了来自中国不同地区的9个剧毒鹅膏菌的核糖体内转录间隔区(ITS)核苷酸序列.以湖南鹅膏为外类群,用ITS序列构建了系统进化树.结果表明:两个不同产地的欧氏鹅膏存在一定的差异,但仍可聚为同一组;欧氏鹅膏与其它几种剧毒鹅膏的亲缘关系较远;两个根据形态特征鉴定为灰花纹鹅膏的标本可能是两个不同的种;欧氏鹅膏、致命鹅膏和黄盖鹅膏白色变种这3个产生白色子实体的种系统演化上不是同源的.     

Quantifying climate–growth relationships at the stand level in a mature mixed‐species conifer forest

A range of environmental factors regulate tree growth; however, climate is generally thought to most strongly influence year‐to‐year variability in growth. Numerous dendrochronological (tree‐ring) studies have identified climate factors that influence year‐to‐year variability in growth for given tree species and location. However, traditional dendrochronology methods have limitations that prevent them from adequately assessing stand‐level (as opposed to species‐level) growth. We argue that stand‐level growth analyses provide a more meaningful assessment of forest response to climate fluctuations, as well as the management options that may be employed to sustain forest productivity. Working in a mature, mixed‐species stand at the Howland Research Forest of central Maine, USA, we used two alternatives to traditional dendrochronological analyses by (1) selecting trees for coring using a stratified (by size and species), random sampling method that ensures a representative sample of the stand, and (2) converting ring widths to biomass increments, which once summed, produced a representation of stand‐level growth, while maintaining species identities or canopy position if needed. We then tested the relative influence of seasonal climate variables on year‐to‐year variability in the biomass increment using generalized least squares regression, while accounting for temporal autocorrelation. Our results indicate that stand‐level growth responded most strongly to previous summer and current spring climate variables, resulting from a combination of individualistic climate responses occurring at the species‐ and canopy‐position level. Our climate models were better fit to stand‐level biomass increment than to species‐level or canopy‐position summaries. The relative growth responses (i.e., percent change) predicted from the most influential climate variables indicate stand‐level growth varies less from to year‐to‐year than species‐level or canopy‐position growth responses. By assessing stand‐level growth response to climate, we provide an alternative perspective on climate–growth relationships of forests, improving our understanding of forest growth dynamics under a fluctuating climate.